[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2788":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"view_count":15,"doi":25,"paper":26,"created_at":57},2788,"Integrated satellite monitoring and field validation of the periodically outbursting glacier-dammed lake Nedre Demmevatnet, Norway","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fegusphere-2026-5025","Abstract. Glacial Lake Outburst Floods (GLOFs) present a significant hazard in warming alpine environments, but detailed, sub-seasonal studies of ice-dammed glacier lakes remain rare due to data scarcity. To overcome this challenge, we reconstruct nearly a decade (2016–2025) of drainage timings, outburst volumes, lake levels, and automated, machine learning-based sub-seasonal lake refilling cycles at the ice-dammed lake Nedre Demmevatnet (southwestern Norway), dammed by the glacier Rembesdalskåka, an outlet glacier of the Hardangerjøkulen ice cap. By integrating publicly available satellite and meteorological datasets, we evaluate remote sensing capabilities and establish an error budget for tracking a small and highly dynamic water body. We validate our spaceborne findings using field measurements, including water-level loggers, time-lapse cameras, a local automatic weather station, and high-resolution UAV photogrammetry, complemented by PlanetScope imagery. Combining Sentinel-1 and Sentinel-2 imagery, we constrain GLOF drainage windows to ± 2 days. Lake volume sensitivity tests revealed that while satellite outline errors are minor (2.6–4.2 %), using the static regional digital elevation model ArcticDEM (2014) causes a 25.5 % volume underestimation compared to our 2022 UAV bathymetry due to rapid ice-dam retreat and lakebed erosion. Crucially, the time gap between the last cloud-free satellite image and the GLOF introduces a relative daily volume underestimation of 1.7 %, which scales up significantly during cloudy periods. Our validated multi-sensor remote sensing approach enables valuable glaciological insights, revealing that GLOF timings shifted earlier by an average of 10 days, alongside shortened refilling periods over the past 9 years. Between 2016 and 2022, pre-GLOF lake levels reached 1236–1239 m a.s.l., closely matching the theoretical hydrostatic flotation threshold. In contrast, the 2023 event drained at approximately 1224 m a.s.l. – more than 10 m below this threshold – following a shortened melt period indicated by fewer positive degree days, possibly due to opening of subglacial channels through melt. Finally, we synthesize the workflow developed and tested on our case study into an operational framework that facilitates transferability to other rapidly changing ice-dammed lakes.","摘要：冰川湖溃决洪水（GLOFs）在变暖的高山环境中构成重大危害，但由于数据稀缺，针对冰坝冰川湖的详细次季节研究仍然很少。为克服这一挑战，我们重建了冰坝湖Nedre Demmevatnet（挪威西南部）近十年（2016—2025年）的排水时间、溃决水量、湖泊水位以及基于机器学习的自动化次季节湖泊再蓄水周期。该湖由Hardangerjøkulen冰帽的溢出冰川Rembesdalskåka所阻塞。通过整合公开可用的卫星和气象数据集，我们评估了遥感能力，并建立了追踪一个小型且高度动态水体的误差预算。我们利用实地测量验证了星载观测结果，包括水位记录仪、延时相机、当地自动气象站和高分辨率无人机摄影测量，并辅以PlanetScope影像。结合Sentinel-1和Sentinel-2影像，我们将GLOF排水窗口限定在±2天以内。湖泊体积敏感性测试表明，虽然卫星轮廓误差较小（2.6—4.2%），但由于冰坝快速退缩和湖床侵蚀，使用静态区域数字高程模型ArcticDEM（2014年）会导致体积较我们的2022年无人机测深结果低估25.5%。至关重要的是，最后一幅无云卫星影像与GLOF之间的时间间隔会导致相对日体积低估1.7%，在多云时段这一误差会显著放大。我们经过验证的多传感器遥感方法带来了有价值的冰川学认识，揭示了过去9年中GLOF发生时间平均提前了10天，同时再蓄水期缩短。2016年至2022年间，GLOF前湖泊水位达到海拔1236—1239 m，与理论静水浮力阈值密切吻合。相比之下，2023年事件在海拔约1224 m处排水——低于该阈值超过10 m——此前融化期缩短，表现为正积温日数减少，可能是由于融化导致冰下通道打开。最后，我们将本案例研究中开发和测试的工作流程综合为一个操作框架，以促进其向其他快速变化的冰坝湖推广应用。",null,"OpenAlex","2026-09-16T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"冰川湖溃决遥感监测研究，属冰川水文与灾害领域，与三农、农业信息化、智慧农业无直接关联，不建议进入每日精选。",[19],{"name":10,"url":6},[21,22,23,24],"遥感监测","卫星遥感","灾害预警","冰川湖","10.5194\u002Fegusphere-2026-5025",{"doi":25,"openalex_id":27,"authors":28,"venue":9,"cited_by_count":15,"oa_url":49,"card":50,"direction":54,"ingested_from":56},"W7213228080",[29,31,34,37,40,43,46],{"name":30,"orcid":9},"Ronja Lappe",{"name":32,"orcid":33},"Ursula Enzenhofer","https:\u002F\u002Forcid.org\u002F0009-0005-4802-1243",{"name":35,"orcid":36},"Pascal E. Egli","https:\u002F\u002Forcid.org\u002F0000-0003-2549-8362",{"name":38,"orcid":39},"Yongmei Gong","https:\u002F\u002Forcid.org\u002F0000-0002-3839-5824",{"name":41,"orcid":42},"Liss M. Andreassen","https:\u002F\u002Forcid.org\u002F0000-0001-6494-4252",{"name":44,"orcid":45},"Andreas Kääb","https:\u002F\u002Forcid.org\u002F0000-0002-6017-6564",{"name":47,"orcid":48},"Martina Calovi","https:\u002F\u002Forcid.org\u002F0000-0002-2317-1190","https:\u002F\u002Fegusphere.copernicus.org\u002Fpreprints\u002F2026\u002Fegusphere-2026-5025\u002Fegusphere-2026-5025.pdf",{"tldr":51,"method":52,"finding":53,"direction":54,"opportunity":55},"结合卫星与实地观测重建挪威冰坝湖近十年溃决周期与水量，并建立可迁移监测框架。","Sentinel-1\u002F2、PlanetScope、UAV摄影测量、水位记录仪与气","溃决时间提前约10天，2023年溃决水位低于浮力阈值10米以上。","农业遥感与作物表型","可将该多源遥感与误差预算框架迁移至其他冰坝湖，并探索云覆盖下水量估算的改进方法。","openalex","2026-09-17T23:30:34.612397Z"]